7 Tips for High Value Analytics
Eric Enge gives you 10 key steps for maximizing your analytics investment, explaining how to overcome some of the limitations of analytics.
Eric Enge gives you 10 key steps for maximizing your analytics investment, explaining how to overcome some of the limitations of analytics.
The analytics industry continues to grow, and more and more Webmasters and Web site owners are relying on analytics tools to provide them with information on how their Web sites are performing. This article will discuss some of the biggest issues faced by companies trying to get the most out of a Web analytics solution.
For many Webmasters, analytics activities are limited to checking basic traffic numbers, such as the number of visitors, unique visitors, and page views. These are great numbers to know, but this is not where high value analytics lie.
In addition, many organizations have their analytics work done in a silo, separate from the rest of their organization. The person, or people, who look at the analytics do their own thing, get some value from it, and then move on. Once again, this approach results in limiting the benefits of Web analytics.
Another issue is the tendency to assume analytics data is always accurate. It is, after all, a computer program measuring a variety of signals that are coming into it from computer hardware – so there should be no errors, right? Unfortunately, as I learned in a recent analytics study we did, this is far from the case. There are, however, ways to deal with the accuracy limitations.
You want to focus your analytics effort on meeting the objectives of your Web site and not on anything else. Given the complexity of analytics, it is easy to get lost in investigating little mysteries instead of focusing on things that make you money. Being clear on your site objectives helps you get around that.
This ends up being the second major component of maintaining your focus when using Web analytics. Cruising around reading canned reports is not the answer (this is what Dennis Mortensen refers to as report surfing). The way to go is to focus on those measurements that provide insight into your business and tell you how your Web site is performing. Attempt to do this up front, and then update your selected KPIs as you learn more about the information you can extract about Web site performance from your analytics program.
At the heart of this rule is one simple fact: High value analytics is hard. You can’t really think of it as taking an off-the-shelf tool, installing it, reading the reports, and then you’re done. Organizations that get the highest ROI on analytics are those that have really smart people focused on deriving value from their tools
You need the right type of people to do this work, too. The business analyst who can do this work well will be a person who has a sharp technical aptitude, as well as a strong marketing and business sense. This person must have both pieces of the puzzle in place to be well suited for this type of work.
Not acting on actionable data is a common problem in many companies. To deal with actionable data in your business requires a cultural commitment to act upon the data as appropriate. For example, if the site’s sales conversion rate drops suddenly by 30 percent, people must be ready to act on this information.
Perhaps marketing needs to investigate whether or not competitors have dropped prices, or management may need to reconsider a recent change in the terms and conditions offered on your site. Sudden KPI changes can affect many different departments. The key is to set up the organization so everyone is looking at the key numbers affecting them, and accept that responding to significant changes in the numbers is part of their job.
The best way to deal with this is to carefully verify your implementation. Treat the addition and/or modification of your analytics JavaScript tags the same way you would any other software development process. This is a source of error in analytics that is completely under your control, so take the time to eliminate it from the picture.
There are many such sources of error, and each analytics package decides how to deal with these types of anomalies in different ways. The end result is many judgment calls, some of which are going to be wrong. In spite of these errors, the data you get still has incredible value, but you have to limit the scope of how these errors affect you.
One way to do this is to use alternative types of tools to cross check your data as much as possible. For example, you wouldn’t use your analytics solution to count the number of orders you get from your PPC campaign, as it would miss some of the orders.
For this, you are better off tagging the end of the URL used in your PPC ads with parameters that your Web application can read during the ordering process. Then you can use your Web application to tally up the total orders, focusing your Web analytics on other tasks it does better than absolute measurement.
What’s that, you ask? Web analytics are great at relative measurement. If the tool provides you with a set of numbers over time, and you look at relative changes in those numbers, you will be looking at very useful and very accurate information. More on this in my next point.
How much can you gain from this? Think of it this way. No matter how experienced a marketer you may be, the chances of designing the penultimate marketing campaign, ad copy, keyword buys, landing pages, etc., on the first try using only your experience is essentially zero. Virtually every Web site can benefit from doing this type of testing.
Of course, testing is a non-trivial investment, and you need to have a really good business analyst on board to get the best results.
As I said, high value analytics is hard. Of course, for smaller Web sites, it is difficult to justify making the investment to do some of the things I outlined above. But as your site’s revenue base grows, analytics can offer a very high ROI on your investment in the tools and the people using them. Keep these seven key steps in mind as you begin that journey, and last of all, be patient.
Finding the optimum way to use analytics on a relatively large site requires experimentation and exploration. Start with the right approach, be patient, and evolve your strategy as you learn more about your Web site, your customers, and the analytics tool you are using.